Non-Traditional Challenges To Achieving Data Quality (Part 5)

This is the last posting in a 5 part series on the non-traditional challenges to achieving data quality. In Part 4, I reviewed the Data Quality Perception Gap. In this post, I will conclude with the Delivery Gap.

The Data Quality Delivery Gap
Once we have successfully marketed, positioned and sold our Data Quality solution, we must shift our focus to delivery. The surest way to secure additional business is to gain customer confidence and there is no better way to do this than through demonstrated competence. While there are many variables that can impact delivery effectiveness, of those that we can control, skills are the most critical. This brings us to the seventh non-traditional challenge…….successful data quality projects can be delivered with generalists. If the business needs an experienced product manager, they don’t hire a payroll specialist. Then why staff a data quality role with an accountant, or a sales operations manager, or an SQL developer? Yet, this is often what happens, and when the effort fails it is at the expense of data quality’s reputation.

But when it comes to effective data quality delivery, having the right skills is only part of the human resource equation. Which brings us to the 8th and final non-traditional challenge……data quality professionals are not equipped with the proper mindset. In a nut shell, data quality success should not be measured by the amount of data defects cleansed, but rather the degree of business improvement achieved. Having data quality professionals that understand and embrace this perspective is integral to any meaningful data quality success.

If data quality is to claim its position as a valued business discipline, we need to recognize that there is more to it than just getting a few smart people in a room. Doing otherwise devalues the proposition and diminishes our profession.